Unveiling Off-Target Mutations in CRISPR Guide RNAs: Implications for Gene Region Specificity.

The revolutionary CRISPR-Cas9 technology has revolutionized genetic engineering, and it holds immense potential for therapeutic interventions. However, the presence of off-target mutations and mismatch capacity poses significant challenges to its safe and precise implementation. In this study, we explore the implications of off-target effects on critical gene regions, including exons, introns, and intergenic regions. Leveraging a benchmark dataset and using innovative data preprocessing techniques, we have put forth the advantages of categorical encoding over one-hot encoding in training machine learning classifiers. Crucially, we use latent class analysis (LCA) to uncover subclasses within the off-target range, revealing distinct patterns of gene region disruption. Our comprehensive approach not only highlights the critical role of model complexity in CRISPR applications but also offers a transformative off-target scoring procedure based on ML classifiers and LCA. By bridging the gap between traditional target-off scoring and comprehensive model analysis, our study advances the understanding of off-target effects and opens new avenues for precision genome editing in diverse biological contexts. This work represents a crucial step toward ensuring the safety and efficacy of CRISPR-based therapies, underscoring the importance of responsible genetic manipulation for future therapeutic applications.

Psychometric evaluation of the Social Support Questionnaire for Transactions in Turkish gender-based violence sample.

AIM: This study aims to investigate the reliability and predictive validity of the Social Support Questionnaire for Transactions (SSQT) scale. DESIGN: A psychometric design using cross-sectional data. METHOD: This cross-sectional descriptive study was conducted between February-June 2021 using snowball sampling through an online survey panel. 204 Turkish survivors of gender-based violence (GBV) participated in the research. RESULTS: The mean age of participants was 35.66 ± 12.50. Exploratory and confirmatory factor analysis examined the construct validity of the SSQT scale. The principle axis factoring (PAF) estimation method was performed, including oblique rotation (Promax) for EFA, and the diagonally weighted least squares (DWLS) estimation method was used for CFA. Test-retest reliability coefficients (r) were moderate to excellent, ranging from 0.48 to 0.88. The analyzes supported the 5-factor solution, and the reliability was evaluated with Cronbach's Alpha coefficients for Social Friendship, Daily Emotional Support, Problem-Oriented Emotional Support, Daily Instrumental Support, and Problem-Focused Instrumental Support sub-dimensions, and the total score of SSQT showing 0.87, 0.84, 0.90, 0.73, 0.83, and 0.93, respectively. The relationships between sub-dimensions of SSQT showed moderate positive correlations ranging from 0.40 to 0.60. There were weak negative correlations between SSQT and PHQ-9, PHQ-15 and GAD-7, ranging from -0.20 to -0.34, which shows the external validity of the SSQT. CONCLUSION: The relationships between sub-dimensions of SSQT and PHQ-9, PHQ-15, GAD-7 are given in the results support using the SSQT scale as a research and clinical instrument for assessing women who had experienced GBV and have/have not received social support in Turkish culture.

Evaluation of treatment responses among subgroups of breast cancer patients receiving neoadjuvant chemotherapy.

BACKGROUND: Breast MRIs are helpful for determining treatment plans, responses, and prospective survival analyses. In this retrospective cross-sectional study, we compared the preoperative MRI treatment response to neoadjuvant chemotherapy (NAC) administration with the postoperative pathological response in breast cancer patients. MATERIALS AND METHODS: We analyzed data from 108 hospitalized patients receiving NAC between 2020 and 2022. We used MRI to evaluate the treatment response to NAC in patients with locally advanced breast cancers who had not received any prior treatment. We recorded the longest diameter of the primary tumor and the numbers of secondary tumors and axillary lymph nodes. In addition, we examined the correlation between the MRI response rate and pathological specimen results. RESULTS: In our subgroup analyses, we found the best pathological response in patients with luminal B (Ki-67 index >14%) breast cancer and positivity for both hormone receptor and HER-2 markers. After comparing the pathological and radiological treatment responses in tumors and lymph nodes, the sensitivities were 90.3% for the pathological assessment and 42.8% for the radiological assessment, while the accuracies were 84.2% for the pathological assessment and 61.1% for the radiological assessment. CONCLUSION: Using MRI techniques and sequence intervals and examining the histopathological characteristics of tumors may help increase the accuracy of the pathological complete response.